Stata 15 help for cs

[R] epitab -- Tables for epidemiologists (cs and csi)

Syntax

cs var_case var_exposed [if] [in] [weight] [, cs_options]

csi #a #b #c #d [, csi_options]

cs_options Description ------------------------------------------------------------------------- Options by(varlist [, missing]) stratify on varlist estandard combine external weights with within-stratum statistics istandard combine internal weights with within-stratum statistics standard(varname) combine user-specified weights with within-stratum statistics pool display pooled estimate nocrude do not display crude estimate nohom do not display homogeneity test rd calculate standardized risk difference binomial(varname) number of subjects variable or report odds ratio woolf use Woolf approximation to calculate SE and CI of the odds ratio exact calculate Fisher's exact p level(#) set confidence level; default is level(95) -------------------------------------------------------------------------

csi_options Description ------------------------------------------------------------------------- or report odds ratio woolf use Woolf approximation to calculate SE and CI of the odds ratio exact calculate Fisher's exact p level(#) set confidence level; default is level(95) ------------------------------------------------------------------------- fweights are allowed; see weight.

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cs

Statistics > Epidemiology and related > Tables for epidemiologists > Cohort study risk-ratio etc.

csi

Statistics > Epidemiology and related > Tables for epidemiologists > Cohort study risk-ratio etc. calculator

Description

cs is used with cohort study data with equal follow-up time per subject and sometimes with cross-sectional data. Risk is then the proportion of subjects who become cases. It calculates point estimates and confidence intervals for the risk difference, risk ratio, and (optionally) the odds ratio, along with attributable or prevented fractions for the exposed and total population. csi is the immediate form of cs; see immed. Also see [R] logistic for related commands.

Options for cs

+---------+ ----+ Options +----------------------------------------------------------

by(varlist [, missing]) specifies that the tables be stratified on varlist. Missing categories in varlist are omitted from the stratified analysis, unless option missing is specified within by(). Within-stratum statistics are shown then combined with Mantel-Haenszel weights. If estandard, istandard, or standard() is also specified (see below), the weights specified are used in place of Mantel-Haenszel weights.

estandard, istandard, and standard(varname) request that within-stratum statistics be combined with external, internal, or user-specified weights to produce a standardized estimate. These options are mutually exclusive and can be used only when by() is also specified. (When by() is specified without one of these options, Mantel-Haenszel weights are used.)

estandard external weights are the total number of unexposed.

istandard internal weights are the total number of exposed controls. istandard can be used to produce, among other things, standardized mortality ratios (SMRs).

standard(varname) allows user-specified weights. varname must contain a constant within stratum and be nonnegative. The scale of varname is irrelevant.

pool specifies that, in a stratified analysis, the directly pooled estimate also be displayed. The pooled estimate is a weighted average of the stratum-specific estimates using inverse-variance weights, which are the inverse of the variance of the stratum-specific estimate. pool is relevant only if by() is also specified.

nocrude specifies that in a stratified analysis the crude estimate -- an estimate obtained without regard to strata -- not be displayed. nocrude is relevant only if by() is also specified.

nohom specifies that a chi-squared test of homogeneity not be included in the output of a stratified analysis. This tests whether the exposure effect is the same across strata and can be performed for any pooled estimate -- directly pooled or Mantel-Haenszel. nohom is relevant only if by() is also specified.

rd may be used only with estandard, istandard, or standard(). It requests that cs calculate the standardized risk difference rather than the default risk ratio.

binomial(varname) supplies the number of subjects (cases plus controls) for binomial frequency records. For individual and simple frequency records, this option is not used.

or reports the calculation of the odds ratio in addition to the risk ratio if by() is not specified. With by(), or specifies that a Mantel-Haenszel estimate of the combined odds ratio be made rather than the Mantel-Haenszel estimate of the risk ratio. In either case, this is the same calculation that would be made by cc and cci. Typically, cc, cci, or tabodds is preferred for calculating odds ratios.

woolf requests that the Woolf (1955) approximation, also known as the Taylor expansion, be used for calculating the standard error and confidence interval for the odds ratio. By default, cs with the or option reports the Cornfield (1956) interval.

exact requests that Fisher's exact p be calculated rather than the chi-squared and its significance level. We recommend specifying exact whenever samples are small. When the least-frequent cell contains 1,000 cases or more, there will be no appreciable difference between the exact significance level and the significance level based on the chi-squared, but the exact significance level will take considerably longer to calculate. exact does not affect whether exact confidence intervals are calculated. Commands always calculate exact confidence intervals where they can, unless cornfield or woolf is specified.

level(#) specifies the confidence level, as a percentage, for confidence intervals. The default is level(95) or as set by set level.

Options for csi

or reports the calculation of the odds ratio in addition to the risk ratio if by() is not specified. With by(), or specifies that a Mantel-Haenszel estimate of the combined odds ratio be made rather than the Mantel-Haenszel estimate of the risk ratio. In either case, this is the same calculation that would be made by cc and cci. Typically, cc, cci, or tabodds is preferred for calculating odds ratios.

woolf requests that the Woolf (1955) approximation, also known as the Taylor expansion, be used for calculating the standard error and confidence interval for the odds ratio. By default, csi with the or option reports the Cornfield (1956) interval.

exact requests that Fisher's exact p be calculated rather than the chi-squared and its significance level. We recommend specifying exact whenever samples are small. When the least-frequent cell contains 1,000 cases or more, there will be no appreciable difference between the exact significance level and the significance level based on the chi-squared, but the exact significance level will take considerably longer to calculate. exact does not affect whether exact confidence intervals are calculated. Commands always calculate exact confidence intervals where they can, unless cornfield or woolf is specified.

level(#) specifies the confidence level, as a percentage, for confidence intervals. The default is level(95) or as set by set level.

Examples

--------------------------------------------------------------------------- Setup . webuse csxmpl

List the data . list

Calculate risk differences, risk ratios, etc. . cs case exp [fw=pop]

Immediate form of above command . csi 7 12 9 2

Same as above, but calculate Fisher's exact p rather than the chi-squared . csi 7 12 9 2, exact

Calculate risk differences, risk ratios, etc., and report the odds ratio . cs case exp [fw=pop], or

--------------------------------------------------------------------------- Setup . webuse ugdp

List the data . list

Perform stratified analysis of cumulative incidence data . cs case exposed [fw=pop], by(age)

Same as above, but report the odds ratio, rather than the risk ratio . cs case exposed [fw=pop], by(age) or

Perform stratified analysis using internally weighted standardized estimates . cs case exposed [fw=pop], by(age) istandard

Perform stratified analysis using externally weighted standardized estimates . cs case exposed [fw=pop], by(age) estandard

Create a variable that is always equal to 1 . generate wgt = 1

Perform stratified analysis of the standardized risk ratio, weighting each age category equally . cs case exposed [fw=pop], by(age) standard(wgt)

Perform stratified analysis of the standardized risk difference, weighting each age category equally . cs case exposed [fw=pop], by(age) standard(wgt) rd ---------------------------------------------------------------------------

Video example

Risk ratios calculator

Stored results

cs and csi store the following in r():

Scalars r(p) two-sided p-value r(rd) risk difference r(lb_rd) lower bound of CI for rd r(ub_rd) upper bound of CI for rd r(rr) risk ratio r(lb_rr) lower bound of CI for rr r(ub_rr) upper bound of CI for rr r(or) odds ratio r(lb_or) lower bound of CI for or r(ub_or) upper bound of CI for or r(afe) attributable (prev.) fraction among exposed r(lb_afe) lower bound of CI for afe r(ub_afe) upper bound of CI for afe r(afp) attributable fraction for the population r(crude) crude estimate (cs only) r(lb_crude) lower bound of CI for crude r(ub_crude) upper bound of CI for crude r(pooled) pooled estimate (cs only) r(lb_pooled) lower bound of CI for pooled r(ub_pooled) upper bound of CI for pooled r(chi2_mh) Mantel-Haenszel heterogeneity chi-squared (cs only) r(chi2_p) pooled heterogeneity chi-squared r(df) degrees of freedom (cs only) r(chi2) chi-squared r(p_exact) 2-sided Fisher's exact p (exact only) r(p1_exact) 1-sided Fisher's exact p (exact only)

References

Cornfield, J. 1956. A statistical problem arising from retrospective studies. In Vol. 4 of Proceedings of the Third Berkeley Symposium, ed. J. Neyman, 135-148. Berkeley, CA: University of California Press.

Woolf, B. 1955. On estimating the relation between blood group disease. Annals of Human Genetics 19: 251-253. Reprinted in Evolution of Epidemiologic Ideas: Annotated Readings on Concepts and Methods, ed. S. Greenland, pp. 108-110. Newton Lower Falls, MA: Epidemiology Resources.


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